I tried regionprops but it is giving out more than one centroid and I need the centre of gravity of the entire image. Thank you.
MATLAB: How to find the centre of gravity of an image
image processing
Related Solutions
Simple.
- Threshold the image to form a binary image.
- Do a morphological closing to close gaps
- Fill holes
- Throw out small blobs
- Take convex hull
- Call regionprops to find centroids.
Try this:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 20;%===============================================================================
% Read in gray scale demo image.
folder = pwd; % Determine where demo folder is (works with all versions).
baseFileName = 'imperfect circles.jpg';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endendrgbImage = imread(fullFileName);% Display the image.
subplot(2, 3, 1);imshow(rgbImage, []);title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');hp = impixelinfo();% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(rgbImage)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(rgbImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage = rgbImage(:, :, 2); % Take green channel.
else grayImage = rgbImage; % It's already gray scale.
end% Now it's gray scale with range of 0 to 255.
% Display the histogram of the image.
subplot(2, 3, 2);[counts, binLocations] = imhist(grayImage);% Suppress bin 1 because it's so tall
counts(1) = 0;bar(binLocations, counts);grid on;title('Histogram of Image', 'FontSize', fontSize, 'Interpreter', 'None');%------------------------------------------------------------------------------
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;% Binarize the image
% Get the mask where the region is solid.
binaryImage = grayImage > 128;% Crop off last 2 lines. For some reason, the next to the last line is all white. Set them equal to false.
binaryImage(end-1:end, :) = false; % Blacken last 2 lines.
% Do a morphological closing to connect lines
se = strel('disk', 5, 0);binaryImage = imclose(binaryImage, se);% Fill blobs:
binaryImage = imfill(binaryImage, 'holes');% Display the image.subplot(2, 3, 3);imshow(binaryImage, []);title('Initial Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');hp = impixelinfo();drawnow;% Extract only those larger than 1000 pixels in area
binaryImage = bwareaopen(binaryImage, 1000);% Display the image.subplot(2, 3, 4);imshow(binaryImage, []);title('Closed Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');drawnow;% Extract only those larger than 1000 pixels in areabinaryImage = bwconvhull(binaryImage, 'objects');% Display the image.subplot(2, 3, 5);imshow(binaryImage, []);title('Final Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');drawnow;% Use it to mask the original image.
finalImage = grayImage; % Initialize
finalImage(~binaryImage) = 0; % Erase outside the mask.
% Display the image.subplot(2, 3, 6);imshow(finalImage, []);title('Final, Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');% bwboundaries() returns a cell array, where each cell contains the row/column coordinates for an object in the image.
% Plot the borders of all the clusters on the original grayscale image using the coordinates returned by bwboundaries.
title('Outlines, from bwboundaries()', 'FontSize', fontSize); axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
hold on;boundaries = bwboundaries(binaryImage);numberOfBoundaries = size(boundaries, 1);for k = 1 : numberOfBoundaries thisBoundary = boundaries{k}; plot(thisBoundary(:,2), thisBoundary(:,1), 'g', 'LineWidth', 2);endhold off;% Find the centroids
props = regionprops(binaryImage, 'Centroid', 'EquivDiameter');xyCentroids = [props.Centroid];xCentroids = xyCentroids(1:2:end)yCentroids = xyCentroids(2:2:end)% Plot centroids over the image with a large red cross.
hold on;for k = 1 : length(xCentroids) thisX = xCentroids(k); thisY = yCentroids(k); thisDiameter = props(k).EquivDiameter; plot(thisX, thisY, 'r+', 'MarkerSize', thisDiameter, 'LineWidth', 2);end
Vishakha:
You might have to take just one color channel, then get rid of the local intensity variations with a bottom hat filter. Then threshold and call bwareafilt() to get rid of blobs bigger or smaller than the known size of the fibers. Then call bwlabel() to count the number of fibers.
Try this for a start - adapt as needed:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format short g;format compact;fontSize = 25;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'netmuscle.jpg';% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);%===============================================================================% Read in a demo image.
grayImage = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(grayImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage = grayImage(:, :, 3); % Take blue channel.
end% Display the image.
subplot(1, 2, 1);imshow(grayImage, []);axis on;axis image;caption = sprintf('Original Gray Scale Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;% Do a bottom hat filter to find the small dark spots.
subplot(1, 2, 2);histogram(grayImage);grid on;se = strel('disk', 15);filteredImage = imbothat(grayImage, se);% Display the image.imshow(filteredImage, []);histogram(filteredImage);grid on;% Binarize the image.
% binaryImage = imbinarize(grayImage);
binaryImage = filteredImage >35; % Dtermine number from histogram.
% Make sure there are blobs only between 100 and 800 pixels.
binaryImage = bwareafilt(binaryImage, [100, 800]);% Display the image.subplot(1, 2, 2);imshow(binaryImage, []);axis on;axis image;caption = sprintf('Binary Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Label the image
[labeledImage, numBlobs] = bwlabel(binaryImage);% Make measurements of bounding box
props = regionprops(labeledImage, 'Area');allAreas = [props.Area]sortedAread = sort(allAreas)caption = sprintf('Binary Image with %d Muscle Fibers', numBlobs);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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